Many organizations create and deploy systems such as Enterprise Data Warehouses (EDW) to serve as the single source of corporate data for business intelligence (BI). EDWs expected to scale to enormous data volumes (hundreds of terabytes) and also expected to perform well under increasingly mixed and complex workloads, including batch and incremental data loads, batch reports, and complex ad hoc queries. One challenge for a system such as EDW is management of complex workloads to meet stringent performance objectives. For instance, batch load tasks are required to finish within a specified time window before reports or queries can be serviced. Batch reports may issue thousands of “roll up” (aggregation) queries that are required to complete within a specified time window. Ad hoc queries may have user-specified deadlines, priorities, and the like. Workload management addresses the problem of scheduling, admitting, and executing queries, and allocating resources to meet the performance objectives.